In computer tomography, 2-D or 3-D image reconstruction is performed using projection data acquired over a period of time in a scan comprised of a series of projections. Each projection is a snapshot of a patient's organs from a different angle, or perspective, and a scan typically includes hundreds of projections. Prior art methods used to reconstruct images from such data presume the patient and his organs are motionless during the entire scan such that a same fixed object is the subject of all acquired projections. Organ motion such as cardiac motion, blood flow, lung respiration or a patient's restlessness during an acquisition process produces artifacts that appear as a blurring effect in the reconstructed image. Such blurring effects substantially complicate diagnosis or may even lead to inaccurate diagnosis putting the patient's health at risk. Furthermore, repeating a scan in case of a complicated diagnosis due to blurring effects exposes the patient unnecessarily to radiation such as X-rays.
Speeding up data acquisition to reduce the blurring effects of organ motion is not possible with current x-ray tube technology. Therefore, signal processing algorithms accounting for organ motion have to be applied in the image reconstruction process.
Several techniques have been proposed to reduce the effects of organ motion. Srinivas, C. and Costa, M. H. M. in "Motion-compensated CT image reconstruction", Proceedings of the IEEE Ultrasonics Symposium, 1, pp. 849-853, 1994, teach motion compensation using a linear model assuming translation and rotation. In U.S. Pat. No. 5,323,007 issued Jun. 21, 1994, Wernick et al. disclose a method for motion compensation using two projections of an object taken from different locations at different time instances. Organ motion is then measured from known image elements and an image is then corrected by solving a set of linear equations. Other techniques model organ motion as a periodic sequence and take projections at a particular point of the motion cycle or to correct image data using motion trajectories obtained from Fourier harmonics as disclosed in U.S. Pat. No. 5,615,677 to Pelc et al. issued Apr. 1, 1997. However, organ motion is too complex for these methods to substantially reduce the blurring effects and makes the prior art methods useful only in a very limited number of cases. In "Tomographic Reconstruction Of Time Varying Object From Linear Time-Sequential Sampled Projections", Proceedings of the IEEE, 0-7803-1775-0/94, pp. 309-312, 1994, Chiu, Y. H. and Yau, S. F. teach a method for compensating for organ motion by iteratively suppressing motion effects from the projections. This method reduces assumed spectral characteristics of the motion artifacts. The method depends on knowledge of at least some properties of the organ motion and requires a substantial number of iterations to converge, thereby requiring a large amount of computing time. In U.S. Pat. No. 5,671,263 issued Sep. 23, 1997, Ching-Ming discloses another spectral method for motion compensation. A high frequency signal of the organ motion is obtained using a high pass filter. The high frequency signal is then subtracted from the projection signal to remove motion artifacts. Unfortunately, removing high frequency components from the projection signal removes small size spatial structures from the image, as well.
In U.S. Pat. No. 5,806,521 issued Sep. 15, 1998, Morimoto et al. disclose a method for motion compensation based on correlating overlapping converted image data in an ultrasound imaging apparatus. In successive image frames a majority of information results from a same geometry. Due to this redundant information the data of two successive image frames is highly correlated. Organ motion between the acquisition of two frames will result in a shift of the correlation peak of the two frames with respect to each other corresponding to the amount of relative motion. Unfortunately, correlation of the two successive image frames taken from different spatial locations results only in a minor reduction of motion artifacts and, furthermore, may lead to cancellation of image details.
It is an object of the invention to provide a method for tracking organ motion and removing motion artifacts, which overcomes the aforementioned problems and substantially reduces motion artifacts in images of a large variety of CT scans.
It is further an object of the invention to provide a method for tracking organ motion and removing motion artifacts for implementation in current CT systems.